The subject matter discussed in this section should not be assumed to be prior art merely as a result of its mention in this section. Similarly, a problem mentioned in this section or associated with the subject matter provided as background should not be assumed to have been previously recognized in the prior art. The subject matter in this section merely represents different approaches, which in and of themselves can also correspond to implementations of the claimed technology.
The term “motion capture” refers generally to processes that capture movement of a real-world subject in three-dimensional (3D) space and translate that movement into, for example, a digital model or other computer-based representation. Motion capture often involves recognizing and tracking the intentional movement of a user's hand, body, or any other object as it performs a gesture, which can be interpreted by an electronic device as user input or a command.
Most existing motion-capture systems rely on markers or sensors worn by the subject while executing the motion and/or on the strategic placement of numerous cameras in the environment to capture images of the moving subject from different angles. Such systems tend to be expensive to construct. In addition, markers or sensors worn by the subject can be cumbersome and interfere with the subject's natural movement. Further, systems involving large numbers of cameras tend not to operate in real time, due to the volume of data that needs to be analyzed and correlated. Such considerations of cost, complexity and convenience have limited the deployment and use of motion-capture technology.
Consequently, there is a need for an economical approach that captures the motion of objects in real time without attaching sensors or markers thereto.